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Title:
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HYBRID RECOMMENDATION APPROACH BASED
ON A VOTING SYSTEM: EXPERIMENTATION
IN AN EDUCATIONAL CONTEXT |
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Author(s):
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Mohammed Baidada, Khalifa Mansouri and Franck Poirier |
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ISBN:
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978-989-8704-17-7 |
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Editors:
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Miguel Baptista Nunes and Pedro Isaias |
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Year:
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2020 |
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Edition:
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Single |
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Keywords:
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E-Learning, Recommendation System, Content-Based Filtering, Collaborative Filtering, Hybrid Filtering,
Experimentation |
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Type:
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Full |
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First Page:
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31 |
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Last Page:
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38 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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We present in this paper the results of a second experiment that was recently conducted to evaluate a hybrid
recommendation approach in an online learning environment. The approach consists of mixing the two approaches of
content-based filtering and collaborative filtering to improve the relevance of the educational resources recommended to
learners. A first experiment was carried out in 2019 and gave convincing results, which led us to repeat a second
experimentation in order to confirm the results, on the one hand, and on the other hand, to modify the way learners
evaluate the resources by transforming the "like" by a vote from one to five, in order to verify whether this will bring an
improvement in the recommendations. This second experiment was also an opportunity to integrate an engine that guides
learners' searches by adding criteria relating to their preferences and to check their satisfaction with the use of this engine.
The results were globally positive. |
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